Keqing He

A qualitative method for measuring the structural complexity of software systems based on complex networks

How can we effectively measure the complexity of a modern complex software system has been a challenge for software engineers. Complex networks as a branch of complexity science are recently studied across many fields of science, and many large-scale software systems are proved to represent an important class of artificial complex networks. So, we introduce the relevant theories and methods of complex networks to analyze the topological/structural complexity of software systems, which is the key to measuring software complexity. Primarily, basic concepts, operational definitions, and measurement units of all parameters involved are presented respectively. Then, we propose a qualitative measure based on the structure entropy that measures the amount of uncertainty of the structural information, and on the linking weight that measures the influences of interactions or relationships between components of software systems on their overall topologies/structures. Eventually, some examples are used to demonstrate the feasibility and effectiveness of our method.

DESIGN METHODOLOGY OF NETWORKED SOFTWARE EVOLUTION GROWTH BASED ON SOFTWARE PATTERNS

Recently, some new characteristics of complex networks attract the attentions of scientists in different fields, and lead to many kinds of emerging research directions. So far, most of the research work has been limited in discovery of complex network characteristics by structure analysis in large-scale software systems.This paper presents the theoretical basis, design method, algorithms and experiment results of the research. It firstly emphasizes the significance of design method of evolution growth for network topology of Object Oriented (OO) software systems, and argues that the selection and modulation of network models with various topology characteristics will bring un-ignorable effect on the process of design and implementation of OO software systems. Then we analyze the similar discipline of “negation of negation and compromise” between the evolution of network models with different topology characteristics and the development of software modelling methods. According to the analysis of the growth features of software patterns, we propose an object-oriented software network evolution growth method and its algorithms in succession. In addition, we also propose the parameter systems for OO software system metrics based on complex network theory. Based on these parameter systems, it can analyze the features of various nodes, links and local-world, modulate the network topology and guide the software metrics. All these can be helpful to the detailed design, implementation and performance analysis. Finally, we focus on the application of the evolution algorithms and demonstrate it by a case study.Comparing the results from our early experiments with methodologies in empirical software engineering, we believe that the proposed software engineering design method is a computational software engineering approach based on complex network theory. We argue that this method should be greatly beneficial for the design, implementation, modulation and metrics of functionality, structure and performance in large-scale OO software complex system.

A Complexity Metrics Set for Large-Scale Object-Oriented Software Systems

Although traditional software metrics have widely been applied to practical software projects, they have insufficient abilities to measure a large-scale systems complexity at high level so as to provide an overview of the system for developers. So, an adequate metrics set for large-scale software systems that can comprehensively measure the complexity at various levels is still challengeable. First, we summarize universal properties and implicit limitations of recognized object-oriented metric sets in the face of ever-increasing complexities of modern software systems. Large-scale software systems represent an important class of artificial complex networks. Then, from the perspective of software engineering, the main parameters of complex networks are introduced in detail. Furthermore, we integrate these metrics and parameters into a hierarchical complexity metrics set, which can measure the complexity at different levels of a large-scale software system. Eventually, we prove the feasibility of our metrics set through analyzing the data from a software project.

Meta-models of Domain Modeling Framework for Networked Software

Networked software is a complex software system deployed on network environment. Web services are the essential components of Networked software, and reuse in this granularity is especially significant. In this paper, we propose a domain modeling framework for Networked software named O-RGPS, which is a layered network including five layers. O-RGPS models the common requirements of a family of systems, and provides feasible solutions for these requirements by aggregating Web services. We introduce the meta-models of each layer in O-RGPS in detail.

A Hybrid Set of Complexity Metrics for Large-Scale Object-Oriented Software Systems ∗

Large-scale object-oriented (OO) software systems have recently been found to share global network characteristics such as small world and scale free, which go beyond the scope of traditional software measurement and assessment methodologies. To measure the complexity at various levels of granularity, namely graph, class (and object) and source code, we propose a hierarchical set of metrics in terms of coupling and cohesion — the most important characteristics of software, and analyze a sample of 12 open-source OO software systems to empirically validate the set. Experimental results of the correlations between cross-level metrics indicate that the graph measures of our set complement traditional software metrics well from the viewpoint of network thinking, and provide more effective information about fault-prone classes in practice.

Semantic Interoperability Aggregation in Service Requirements Refinement

Semantic refinement of stakeholders’ requirements is a fundamental issue in requirements engineering. Facing with the on-demand collaboration problem among the heterogeneous, autonomous, and dynamic service resources in the Web, service requirements refinement becomes extremely important, and the key issue in service requirements refinement is semantic interoperability aggregation. A method for creating connecting ontologies driven by requirement sign ontology is proposed. Based on connecting ontologies, a method for semantic interoperability aggregation in requirements refinement is proposed. In addition, we discover that the necessary condition for semantic interoperability is semantic similarity, and the sufficient condition is the coverability of the agreed mediation ontology. Based on this viewpoint, a metric framework for calculating semantic interoperability capability is proposed. This methodology can provide a semantic representation mechanism for refining users’ requirements; meanwhile, since users’ requirements in the Web usually originate from different domains, it can also provide semantic interoperability guidance for networked service discovery, and is an effective approach for the realization of on-demand service integration. The methodology will be beneficial in service-oriented software engineering and cloud computing.

A Practical Architecture of Cloudification of Legacy Applications

Cloud computing has been attracting much attention since its birth. How to cloudify software systems especially legacy applications in the cloud era is becoming increasingly important. Based on RGPS meta-model framework and International standards-ISO/IEC 19763, an architecture for cloudification of legacy applications is proposed, which consists of three parts: a Web portal, a SaaS service supermarket, and a SaaS application development platform. In this paper, we take an open source software as an example to illustrate the proposed approach. Based on the architecture and supporting techniques on software virtualization and multi-tenancy, we develop a prototype Cloud CRM to demonstrate the basic procedure for cloudification of legacy applications, as well as the feasibility of the proposed approach.

From collective knowledge to intelligence: pre-requirements analysis of large and complex systems

Requirements engineering is essentially a social collaborative activity in which involved stakeholders have to closely work together to communicate, elicit, negotiate, define, confirm, and finally come up with the requirements for the system to be implemented or upgraded. In the development of large and complex systems, with a huge number of uncertain stakeholders, the requirements engineering process becomes a challenging task due to overwhelming and dynamic social interactions, tradeoffs, and collective decisions made by above stakeholders. Traditional approaches and techniques are deficient in supporting this kind of social interactions in requirements-related activities, and managing the evolving requirements and their traceability caused by the social interactions. This paper proposes to address the challenges in the pre-requirements analysis of large and complex systems by employing the techniques from collective intelligence based on Web 2.0 tools and technologies, which is composed of three steps: first, obtain collective requirements knowledge through collaborative tagging by stakeholders; second, transform collaborative requirement tags into requirement ontologies; third, support collective requirement decision-making (i.e., collective intelligence) based on the requirement ontologies through requirements reasoning.

Towards Representing FCA-based Ontologies in Semantic Web Rule Language

Formal Concept Analysis (FCA) has been widely applied in many fields recently. In this paper, we introduce how a domain ontology can be constructed based on FCA. The consequential ontology constructed in this way is graphically represented as a concept lattice. After constructing FCA-based ontologies, it is necessary to represent the FCAbased ontologies in a formalism for sharing and reasoning. Semantic Web Rule Language(SWRL), a W3C proposal, is an extension with Horn clause rules on OWL. We represent the FCA-based ontologies in SWRL with some extension, which can be more suitable for reasoning.

Ontology application in software component registry to achieve semantic interoperability

The ebXML registry has become one of the most well accepted registry standards for governments and industries. Though originally designed for B2B artifacts, almost any industrial artifact can be registered into an ebXML registry by extending the ebXML registry information model. However, this extensibility also debilitates its interoperability caused by insufficient semantic provided for it. This paper presents our solution to extend semantic for a software component in our development of SCRR system. An attribute ontology of software component is introduced to provide rich semantic information. We also explain how to implement a software component registry based on classification by applying the attribute ontology.